A comprehensive evaluation of CRISPR lineage recorders using TraceQC
Jingyuan HuiD, Hyun-Hwan JeongiD, Rami Al‐OuraniD, Igor L. BadoiD, Weijie ZhangiD, Xiang H.-F. ZhangiD, Zhandong LiuiD
Abstract
The CRISPR-Cas9 genome editing-based lineage tracing system is emerging as a powerful tool to track cell lineages at unprecedented scale and resolution. However, the complexity of CRISPR-Cas9 induced mutations has raised challenges in lineage reconstruction, which requires a unique computational analysis framework. Meanwhile, multiple distinctive CRISPR-based high-throughput lineage recorders have been developed over the years in which the data analysis is incompatible across platforms. To address these challenges, first, we present the TraceQC, a cross-platform open-source package for data processing and quality evaluation of CRISPR lineage tracing data. Second, by using the TraceQC package, we performed a comprehensive analysis across multiple CRISPR lineage recorders to uncover the speed and distribution of CRISPR-induced mutations. Together, this work provides a computational framework for the CRISPR lineage tracing system that should broadly benefit the design and application of this promising technology.
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